Power of heterogeneous computing as a vehicle for implementing E(3) medical decision support systems

A computer system of PCs, workstations, minicomputers etc. connected together via a local area network or wide area network represents a large pool of computational power. Our aim is to use this power for the implementation of an E(3) (efficiency, effectiveness, efficacy) medical decision support system, which can be based on different models, the best providing an explanation together with an accurate and reliable response. One of the most viable among models is decision trees, already used for many medical decision-making purposes. In this paper, we present a parallel implementation of a genetic algorithm on a heterogeneous computing system for the induction of decision trees with the application on solving the mitral valve prolapse syndrome. Our approach can be considered as a good choice for different real-world decision making, with respect to the advantages of our model, especially the great computational power.